So sánh phương pháp

	Semi-supervised Stacking Ensemble (Tăng cường xếp chồng bán giám sát)	Lan truyền nhãn
Lĩnh vực	Học máy	Học máy
Họ	Machine learning	Machine learning
Năm ra đời	2000s–2010s	2002
Người khởi xướng	Combines Wolpert (1992) stacking with semi-supervised learning principles	Zhu, X. & Ghahramani, Z.
Loại	Ensemble (stacked generalization with unlabeled data augmentation)	Graph-based semi-supervised classification
Công trình gốc	Wolpert, D. H. (1992). Stacked generalization. Neural Networks, 5(2), 241–259.	Zhu, X., & Ghahramani, Z. (2002). Learning from labeled and unlabeled data with label propagation. Technical Report CMU-CALD-02-107, Carnegie Mellon University.
Tên gọi khác	SSL stacking, semi-supervised stacked generalization, self-trained stacking, semi-supervised meta-learning ensemble	LP, label spreading, graph-based semi-supervised learning, harmonic label propagation
Liên quan	5	3
Tóm tắt	Semi-supervised Stacking Ensemble extends the classic stacked generalization framework to settings where only a fraction of training examples carry labels. Base learners are first trained on labeled data, then used to assign pseudo-labels to unlabeled examples; the expanded dataset trains stronger base models whose out-of-fold predictions form the input to a meta-learner, yielding a two-tier ensemble that exploits both labeled and unlabeled structure.	Label Propagation is a graph-based semi-supervised learning algorithm introduced by Zhu and Ghahramani in 2002 that spreads class labels from a small set of labeled nodes to a large set of unlabeled nodes by iteratively diffusing label information along the edges of a similarity graph, exploiting the manifold structure of the data.